15 citations · 57 across the 26 of their papers we have counts for
29 papers
Spatially-Attentive Patch-Hierarchical Network with Adaptive Sampling for Motion Deblurring
Maitreya Suin, Kuldeep Purohit, A. N. Rajagopalan
This paper tackles the problem of motion deblurring of dynamic scenes. Although end-to-end fully convolutional designs have recently advanced the state-of-the-art in non-uniform mo…
Zero shot framework for satellite image restoration
Praveen Kandula, A. N. Rajagopalan
Satellite images are typically subject to multiple distortions. Different factors affect the quality of satellite images, including changes in atmosphere, surface reflectance, sun…
Unsupervised haze removal from underwater images
Praveen Kandula, A. N. Rajagopalan
Several supervised networks exist that remove haze information from underwater images using paired datasets and pixel-wise loss functions. However, training these networks requires…
Unsupervised network for low-light enhancement
Praveen Kandula, Maitreya Suin, A. N. Rajagopalan
Supervised networks address the task of low-light enhancement using paired images. However, collecting a wide variety of low-light/clean paired images is tedious as the scene needs…
Exploring the Effectiveness of Mask-Guided Feature Modulation as a Mechanism for Localized Style Editing of Real Images
Snehal Singh Tomar, Maitreya Suin, A. N. Rajagopalan
The success of Deep Generative Models at high-resolution image generation has led to their extensive utilization for style editing of real images. Most existing methods work on the…
Hybrid Transformer Based Feature Fusion for Self-Supervised Monocular Depth Estimation
Snehal Singh Tomar, Maitreya Suin, A. N. Rajagopalan
With an unprecedented increase in the number of agents and systems that aim to navigate the real world using visual cues and the rising impetus for 3D Vision Models, the importance…
Unfolding a blurred image
Kuldeep Purohit, Anshul Shah, A. N. Rajagopalan
We present a solution for the goal of extracting a video from a single motion blurred image to sequentially reconstruct the clear views of a scene as beheld by the camera during th…
Image Superresolution using Scale-Recurrent Dense Network
Kuldeep Purohit, Srimanta Mandal, A. N. Rajagopalan
Recent advances in the design of convolutional neural network (CNN) have yielded significant improvements in the performance of image super-resolution (SR). The boost in performanc…
Deep Networks for Image and Video Super-Resolution
Kuldeep Purohit, Srimanta Mandal, A. N. Rajagopalan
Efficiency of gradient propagation in intermediate layers of convolutional neural networks is of key importance for super-resolution task. To this end, we propose a deep architectu…
Robust Unpaired Single Image Super-Resolution of Faces
Saurabh Goswami, Rajagopalan A. N
We propose an adversarial attack for facial class-specific Single Image Super-Resolution (SISR) methods. Existing attacks, such as the Fast Gradient Sign Method (FGSM) or the Proje…
Image Restoration using Feature-guidance
Maitreya Suin, Kuldeep Purohit, A. N. Rajagopalan
Image restoration is the task of recovering a clean image from a degraded version. In most cases, the degradation is spatially varying, and it requires the restoration network to b…
Adaptive Image Inpainting
Maitreya Suin, Kuldeep Purohit, A. N. Rajagopalan
Image inpainting methods have shown significant improvements by using deep neural networks recently. However, many of these techniques often create distorted structures or blurry t…
Dynamic Scene Video Deblurring using Non-Local Attention
Maitreya Suin, A. N. Rajagopalan
This paper tackles the challenging problem of video deblurring. Most of the existing works depend on implicit or explicit alignment for temporal information fusion which either inc…
Adaptive Single Image Deblurring
Maitreya Suin, Kuldeep Purohit, A. N. Rajagopalan
This paper tackles the problem of dynamic scene deblurring. Although end-to-end fully convolutional designs have recently advanced the state-of-the-art in non-uniform motion deblur…
Mitigating Channel-wise Noise for Single Image Super Resolution
Srimanta Mandal, Kuldeep Purohit, A. N. Rajagopalan
In practice, images can contain different amounts of noise for different color channels, which is not acknowledged by existing super-resolution approaches. In this paper, we propos…
Deep network for rolling shutter rectification
Praveen K, Lokesh Kumar T, A. N. Rajagopalan
CMOS sensors employ row-wise acquisition mechanism while imaging a scene, which can result in undesired motion artifacts known as rolling shutter (RS) distortions in the captured i…
IR Motion Deblurring
Nisha Varghese, Mahesh Mohan M. R., A. N. Rajagopalan
Camera gimbal systems are important in various air or water borne systems for applications such as navigation, target tracking, security and surveillance. A higher steering rate (r…
Spatially-Adaptive Image Restoration using Distortion-Guided Networks
Kuldeep Purohit, Maitreya Suin, A. N. Rajagopalan +1
We present a general learning-based solution for restoring images suffering from spatially-varying degradations. Prior approaches are typically degradation-specific and employ the…
AIM 2020 Challenge on Rendering Realistic Bokeh
Andrey Ignatov, Radu Timofte, Ming Qian +32
This paper reviews the second AIM realistic bokeh effect rendering challenge and provides the description of the proposed solutions and results. The participating teams were solvin…
AIM 2020: Scene Relighting and Illumination Estimation Challenge
Majed El Helou, Ruofan Zhou, Sabine Süsstrunk +34
We review the AIM 2020 challenge on virtual image relighting and illumination estimation. This paper presents the novel VIDIT dataset used in the challenge and the different propos…
Unpaired Image Denoising
Priyatham Kattakinda, A. N. Rajagopalan
Deep learning approaches in image processing predominantly resort to supervised learning. A majority of methods for image denoising are no exception to this rule and hence demand p…
AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
Kai Zhang, Martin Danelljan, Yawei Li +75
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an in…
Spatially-Attentive Patch-Hierarchical Network for Adaptive Motion Deblurring
Maitreya Suin, Kuldeep Purohit, A. N. Rajagopalan
This paper tackles the problem of motion deblurring of dynamic scenes. Although end-to-end fully convolutional designs have recently advanced the state-of-the-art in non-uniform mo…
AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results
Andreas Lugmayr, Martin Danelljan, Radu Timofte +18
This paper reviews the AIM 2019 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting,…